{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 首先导入相应的import工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 首先import必要的模块\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>116</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25.6</td>\n",
       "      <td>0.201</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>78</td>\n",
       "      <td>50</td>\n",
       "      <td>32</td>\n",
       "      <td>88</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.248</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35.3</td>\n",
       "      <td>0.134</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>197</td>\n",
       "      <td>70</td>\n",
       "      <td>45</td>\n",
       "      <td>543</td>\n",
       "      <td>30.5</td>\n",
       "      <td>0.158</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>125</td>\n",
       "      <td>96</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.232</td>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "0          6                           148              72   \n",
       "1          1                            85              66   \n",
       "2          8                           183              64   \n",
       "3          1                            89              66   \n",
       "4          0                           137              40   \n",
       "5          5                           116              74   \n",
       "6          3                            78              50   \n",
       "7         10                           115               0   \n",
       "8          2                           197              70   \n",
       "9          8                           125              96   \n",
       "\n",
       "   Triceps_skin_fold_thickness  serum_insulin   BMI  \\\n",
       "0                           35              0  33.6   \n",
       "1                           29              0  26.6   \n",
       "2                            0              0  23.3   \n",
       "3                           23             94  28.1   \n",
       "4                           35            168  43.1   \n",
       "5                            0              0  25.6   \n",
       "6                           32             88  31.0   \n",
       "7                            0              0  35.3   \n",
       "8                           45            543  30.5   \n",
       "9                            0              0   0.0   \n",
       "\n",
       "   Diabetes_pedigree_function  Age  Target  \n",
       "0                       0.627   50       1  \n",
       "1                       0.351   31       0  \n",
       "2                       0.672   32       1  \n",
       "3                       0.167   21       0  \n",
       "4                       2.288   33       1  \n",
       "5                       0.201   30       0  \n",
       "6                       0.248   26       1  \n",
       "7                       0.134   29       0  \n",
       "8                       0.158   53       1  \n",
       "9                       0.232   54       1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.read_csv('pima-indians-diabetes.csv')\n",
    "train.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: (768, 9)\n"
     ]
    }
   ],
   "source": [
    "print('Train:',train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "pregnants                       768 non-null int64\n",
      "Plasma_glucose_concentration    768 non-null int64\n",
      "blood_pressure                  768 non-null int64\n",
      "Triceps_skin_fold_thickness     768 non-null int64\n",
      "serum_insulin                   768 non-null int64\n",
      "BMI                             768 non-null float64\n",
      "Diabetes_pedigree_function      768 non-null float64\n",
      "Age                             768 non-null int64\n",
      "Target                          768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "# 查看数据的基本信息\n",
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "count  768.000000                    768.000000      768.000000   \n",
       "mean     3.845052                    120.894531       69.105469   \n",
       "std      3.369578                     31.972618       19.355807   \n",
       "min      0.000000                      0.000000        0.000000   \n",
       "25%      1.000000                     99.000000       62.000000   \n",
       "50%      3.000000                    117.000000       72.000000   \n",
       "75%      6.000000                    140.250000       80.000000   \n",
       "max     17.000000                    199.000000      122.000000   \n",
       "\n",
       "       Triceps_skin_fold_thickness  serum_insulin         BMI  \\\n",
       "count                   768.000000     768.000000  768.000000   \n",
       "mean                     20.536458      79.799479   31.992578   \n",
       "std                      15.952218     115.244002    7.884160   \n",
       "min                       0.000000       0.000000    0.000000   \n",
       "25%                       0.000000       0.000000   27.300000   \n",
       "50%                      23.000000      30.500000   32.000000   \n",
       "75%                      32.000000     127.250000   36.600000   \n",
       "max                      99.000000     846.000000   67.100000   \n",
       "\n",
       "       Diabetes_pedigree_function         Age      Target  \n",
       "count                  768.000000  768.000000  768.000000  \n",
       "mean                     0.471876   33.240885    0.348958  \n",
       "std                      0.331329   11.760232    0.476951  \n",
       "min                      0.078000   21.000000    0.000000  \n",
       "25%                      0.243750   24.000000    0.000000  \n",
       "50%                      0.372500   29.000000    0.000000  \n",
       "75%                      0.626250   41.000000    1.000000  \n",
       "max                      2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数值型特征的基本统计量\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plasma_glucose_concentration      5\n",
      "blood_pressure                   35\n",
      "Triceps_skin_fold_thickness     227\n",
      "serum_insulin                   374\n",
      "BMI                              11\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 下列变量的最小值为0时数据无意义：1.血浆葡萄糖浓度，2.舒张压，3.肱二头肌皮褶厚度，4.餐后血清胰岛素，5.体重指标。因此需要找出为0的个数\n",
    "NaN_col_names = ['Plasma_glucose_concentration','blood_pressure','Triceps_skin_fold_thickness','serum_insulin','BMI']\n",
    "print((train[NaN_col_names] == 0).sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.查看每个变量的分布 及其与标签之间的关系"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrances')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 该问题为分类问题，类别型特征直方图可用countplot\n",
    "sns.countplot(train['Target'])\n",
    "plt.xlabel('Diabetes')\n",
    "plt.ylabel('Number of occurrances')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "其中“1”代表得了糖尿病的人数，“0”代表没有得糖尿病的人数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 怀孕次数pregnants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrances')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.countplot(train['pregnants'])\n",
    "plt.xlabel('Number of pregnants')\n",
    "plt.ylabel('Number of occurrances')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 从上图我们可以看出怀孕次数大部分在前面几次。\n",
    "### 但也有怀孕次数有超过17次，在疾病判断案例中，异常值可能意味着得病。\n",
    "### 删除怀孕次数大于10的样本，可以将其删除 train = train[train['pregnants'] < ulimit]  print(train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a257b2390>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x = 'pregnants',hue = 'Target',data = train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "是否得糖尿病与怀孕次数的关系如上图所示："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.Plasma_glucose_concentration\n",
    "血浆葡萄糖的浓度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Plasma_glucose_concentration,kde = False)\n",
    "plt.xlabel('plasma_glucose_concentration')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'plasma_glucose_concentration')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.violinplot(x = 'Target',y = 'Plasma_glucose_concentration',data = train,hue = 'Target')\n",
    "plt.xlabel('Diabetes',fontsize = 12)\n",
    "plt.ylabel('plasma_glucose_concentration',fontsize = 12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a25bdbf50>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['Plasma_glucose_concentration','Target'])['Plasma_glucose_concentration'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind = 'bar',stacked = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.blood_pressure（血压）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frequency')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.blood_pressure,kde = False)\n",
    "plt.xlabel('blood_pressure')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从图中我们可以看出血压主要集中在60-80之间，但也有血压为0的情况，这些血压为0的属于异常数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 血压与糖尿病之间的关系\n",
    "fig = plt.figure()\n",
    "sns.violinplot(x = 'Target',y = 'blood_pressure',data = train,hue = 'Target')\n",
    "plt.xlabel('Diabetes',fontsize = 12)\n",
    "plt.ylabel('blood_pressure',fontsize = 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.Triceps_skin_fold_thickness \n",
    "三头肌皮褶厚度（单位：mm）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frequency')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Triceps_skin_fold_thickness,kde = False)\n",
    "plt.xlabel('Triceps_skin_fold_thickness ')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 三头肌皮褶厚度与糖尿病之间的关系\n",
    "fig = plt.figure()\n",
    "sns.violinplot(x = 'Target',y = 'Triceps_skin_fold_thickness',data = train,hue = 'Target')\n",
    "plt.xlabel('Diabetes',fontsize = 12)\n",
    "plt.ylabel('Triceps_skin_fold_thickness',fontsize = 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a267a9510>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['Triceps_skin_fold_thickness','Target'])['Triceps_skin_fold_thickness'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind = 'bar',stacked = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.serum_insulin\n",
    "餐后血清胰岛素（单位：mm）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frequency')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.serum_insulin,kde = False)\n",
    "plt.xlabel('serum_insulin ')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.violinplot(x = 'Target',y = 'serum_insulin',data = train,hue = 'Target')\n",
    "plt.xlabel('Diabetes',fontsize = 12)\n",
    "plt.ylabel('serum_insulin',fontsize = 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a266e01d0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['serum_insulin','Target'])['serum_insulin'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind = 'bar',stacked = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.BMI\n",
    "体重指数（体重（公斤）/身高（米）^2）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frequency')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.BMI,kde = False)\n",
    "plt.xlabel('BMI ')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从图中我们可以看出BMI有为0的情况，说明可能是缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a27aeed90>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['BMI','Target'])['BMI'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind = 'bar',stacked = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8.Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frequency')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Age, kde = False)\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.violinplot(x = 'Target',y = 'Age',data = train,hue = 'Target')\n",
    "plt.xlabel('Diabetes',fontsize = 12)\n",
    "plt.ylabel('Age',fontsize = 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从图中我们可以看出，年龄在20-30岁的人中得糖尿病的人很少，而得糖尿病的病人的年龄主要集中在30-50岁。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a28620210>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['Age','Target'])['Age'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind = 'bar',stacked = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9.Diabetes_pedigree_function,糖尿病家系作用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'frequency')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Diabetes_pedigree_function,kde = False)\n",
    "plt.xlabel('Diabetes_pedigree_function')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.violinplot(x = 'Target',y = 'Diabetes_pedigree_function',data = train,hue = 'Target')\n",
    "plt.xlabel('Diabetes',fontsize = 12)\n",
    "plt.ylabel('Diabetes_pedigree_function',fontsize = 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a289de350>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['Diabetes_pedigree_function','Target'])['Diabetes_pedigree_function'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind = 'bar',stacked = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.特征之间的相互关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a293a8610>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_corr = train.corr().abs()\n",
    "plt.subplots(figsize = (18,10))\n",
    "sns.heatmap(data_corr,annot = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上图我们可以看出其相关性不是很大，最大的为0.54。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们也可以通过一个for循环将特征表示出来"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Gvgy8Dtw7gnzSUDj9ov1OVf0zsBqYmrPvXWALcBODVSulieRIXfudJKcABzBYPOngOQ/9OfAPVfXjwQKW0uSx1LW/2DWnDoMvp1hfVR/MLe+qehavetGEc5VGSWqIc+qS1BBLXZIaYqlLUkMsdUlqiKUuSQ2x1CWpIZa6JDXkfwGG/fjGlGMB6wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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fu+hCulOvXtG3PS/Jh/tzcd+d5J4kl/X3nZPkX/uTjd07dVi8NGoMdx3tLqU7D/p/AE8mORv4XWAt8Gt0RxVeAD8719HfA5dV1TnAjcB1y1G0NJsVs3eRmraJ7uRn0B0Wvgk4FvhUVf0U+G6S+/v7zwDOAu7rThfCMXSnc5VGjuGuo1Z/zpJXA2clKbqwLp4958xhDwEerqoLlqhEacGcltHR7DLgpqp6cVWtrao1dL9o9ATwe/3c+ynARX3/3cBEkp9N0yR5+XIULs3GcNfRbBOHb6XfRvfjCpN0pwD+CN2ZSJ+qqv+l+4PwviRfBR6kO0e3NHI8K6Q0gyQvqKof9VM3X6T71abvLndd0lw55y7N7O7+B1aeD/y1wa5x45a7JDXIOXdJapDhLkkNMtwlqUGGuyQ1yHCXpAb9P9spzHDvW+3/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in train.columns:\n",
    "    sns.distplot(train[feature],kde = False)\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
